Linked Life Data

17688511

Source:http://linkedlifedata.com/resource/pubmed/id/17688511

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2007-8-10
pubmed:abstractText
In this article, we consider nonparametric regression when covariates are measured with error. Estimation is performed using boosted regression trees, with the sum of the trees forming the estimate of the conditional expectation of the response. Both binary and continuous response regression are investigated. An approach to fitting regression trees when covariates are measured with error is described, and the boosting algorithms consist of its repeated application. The main feature of the approach is that it handles situations where multiple covariates are measured with error. Some simulation results are given as well as its application to data from the Framingham Heart Study.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0006-341X
pubmed:author
pubmed:issnType
Print
pubmed:volume
63
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
586-92
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Boosted regression trees with errors in variables.
pubmed:affiliation
Institute of Basic Medical Sciences, Department of Biostatistics, Boks 1122 Blindern, 0317 Oslo, Norway. j.a.sexton@medisin.uio.no
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't